class_docstr: An abstract bridge class. A bridge defines how state is passed
  between encoder and decoder.
  
  All logic is contained in the `_create` method, which returns an
  initial state for the decoder.
  
  Args:
    encoder_outputs: A namedtuple that corresponds to the the encoder outputs.
    decoder_state_size: An integer or tuple of integers defining the
      state size of the decoder.
code: def __init__(self, encoder_outputs, decoder_state_size, params, mode):
      Configurable.__init__(self, params, mode)
      self.encoder_outputs = encoder_outputs
      self.decoder_state_size = decoder_state_size
      self.batch_size = tf.shape(
          nest.flatten(self.encoder_outputs.final_state)[0]
      )[0]
  
imports: from __future__ import absolute_import
  from __future__ import division
  from __future__ import print_function
  from __future__ import unicode_literals
  import abc
  from pydoc import locate
  import six
  import numpy
  import tensorflow
  from tensorflow.python.util import nest
  from seq2seq.configurable import Configurable
label_desc: Use image node_id 1 to create a new Bridge object from inherited base classes: Configurable with example: obj = Bridge(encoder_outputs, decoder_state_size, params, mode)